Associate Machine Learning Engineer (LLM & NLP)

Duties & Responsibilities

• Develop, fine-tune, and deploy large language models (LLMs) and NLP solutions using APIs such as OpenAI, Claude AI, and similar platforms.
• Implement and enhance Retrieval-Augmented Generation (RAG) systems to improve information retrieval and response quality in AI-driven applications.
• Collaborate with cross-functional teams to integrate ML/NLP models into production systems.
• Contribute to building intelligent agentic AI systems with autonomous decision-making and task management capabilities.
• Support data preprocessing, feature engineering, and model evaluation activities.
• Assist in troubleshooting, debugging, and optimizing deployed ML models.
• Research and stay up-to-date with advancements in LLMs, NLP, and AI frameworks.
• Participate in code reviews and maintain code quality and documentation.

Our Requirements

• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or related field, or equivalent experience.
• Must be able to work between 8:00 AM to 5:00 PM Eastern Time Zone (ET).
• Strong communication in English and collaboration skills.
• 1+ years of experience working with machine learning models, especially in natural language processing (NLP) and large language models.
• Hands-on experience with OpenAI API, Claude AI, or comparable LLM platforms.
• Experience implementing and working with Retrieval-Augmented Generation (RAG) techniques.
• Understanding of agentic AI principles and architectures.
• Strong programming skills in Python and familiarity with ML/NLP frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
• Positive attitude, self-motivated, and eager to learn in a dynamic environment.

What You’ll Receive

• Opportunity to work on cutting-edge international AI projects impacting diverse industries.
• Hands-on experience deploying and optimizing large-scale NLP systems.
• Mentorship from experienced ML engineers and researchers.
• Exposure to latest developments in LLMs, RAG, and autonomous AI systems.
• Career growth and networking opportunities within AI and tech industries.
• Flexible work environment with potential for remote work.